The impact of the 2008/2009 financial crisis on specialist physician activity in Canada
Bibliographic record
Abstract
Fee-for-service physicians are responsible for planning for their retirements, and there is no mandated retirement age. Changes in financial markets may influence how long they remain in practice and how much they choose to work. The 2008 crisis provides a natural experiment to analyze elasticity in physician service supply in response to dramatic financial market changes. We examined quarterly fee-for-service data for specialist physicians over the period from 1999/2000 to 2013/2014 in Canada. We used segmented regression to estimate changes in the number of physicians receiving payments, per-physician service counts, and per-physician payments following the 2008 financial crisis and explored whether patterns differed by physician age. The number of specialist physicians increased more rapidly in the period since 2008 than in earlier years, but increases were largest within the youngest age group, and we observed no evidence of delayed retirement among older physicians. Where changes in service volume and payments were observed, they occurred across all ages and not immediately following the 2008 financial crisis. We conclude that any response to the financial crisis was small compared with demographic shifts in the physician population and changes in payments per service over the same time period.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".